1. Field
This disclosure is generally related to email processing. More specifically, this disclosure is related to calculating prominence values of emails and email participants.
2. Related Art
Email has become an indispensable part of today's information economy. Employees often spend a substantial part of their workday plodding through mountains of email messages whose subject matter can range from the utterly trivial to the extremely important. A fair amount of research has investigated how people perceive the importance of email and email senders/receivers.
One technique to evaluate email importance is based on user surveys and feedback collected from users on their actions taken on the emails, such as response and attachment. This technique is derived from the finding that perceived email importance and reply probability are related to each other. Early results give a good indication of correlations between specific factors and perceived importance. Although a linear regression model for showing correlations can be used for the prediction, the input factors (e.g., “Action request”) are hand-labeled and their derivation is not automatic.
Some recent work has proposed approaches for email prioritization based on automatically derived social network information. For example, an email message from a sender may be assigned a high importance if the recipient frequently receives emails from the sender. However, this technique based on social network features requires a sufficient amount of emails and calculation resources to derive higher-level social network features.